Abstract

Central nervous system (CNS) inflammation involves the generation of inducible cytokines such as interferons (IFNs) and alterations in brain activity, yet the interplay of both is not well understood. Here, we show that in vivo elevation of IFNs by viral brain infection reduced hyperpolarization-activated currents (Ih) in cortical pyramidal neurons. In rodent brain slices directly exposed to type I IFNs, the hyperpolarization-activated cyclic nucleotide (HCN)-gated channel subunit HCN1 was specifically affected. The effect required an intact type I receptor (IFNAR) signaling cascade. Consistent with Ih inhibition, IFNs hyperpolarized the resting membrane potential, shifted the resonance frequency, and increased the membrane impedance. In vivo application of IFN-β to the rat and to the mouse cerebral cortex reduced the power of higher frequencies in the cortical electroencephalographic activity only in the presence of HCN1. In summary, these findings identify HCN1 channels as a novel neural target for type I IFNs providing the possibility to tune neural responses during the complex event of a CNS inflammation.

Introduction

The cytokines interferons (IFN)-α and -β belong to type I IFNs and share receptor and signaling pathways. They are key elements in the mammalian first-line innate immune response because they activate immune cells, stimulate surface molecules, and regulate the differentiation of monocytes (Pestka 2007). In the context of central nervous system (CNS) inflammation, IFN-β is increased in myeloid cells (Prinz et al. 2008) and locally produced by neurons (Delhaye et al. 2006). In turn, all cell types of the CNS respond to type I IFNs (Delhaye et al. 2006; Paul et al. 2007; Detje et al. 2009). Besides these established immunological and antiviral effects, evidence for a neuromodulatory potential of IFNs is growing. For example, during medical treatment, IFNs can lead to various behavioral changes, for example, fatigue, cognitive dysfunction, depressed mood, condensed as sickness behavior (Dantzer et al. 2008). On the cellular level, type I IFNs enhance neuronal excitability in neurons of the cortex, the hippocampus, and the amygdala (Dafny et al. 1996). However, the mechanisms by which type I IFNs impact on neuronal excitability are poorly understood.

In our previous in vitro study, application of IFN-β lead to an increased firing rate and input resistance in cortical neurons (Hadjilambreva et al. 2005). Indirect evidence suggested that the hyperpolarization-activated nonselective cation current (Ih) may serve as a possible molecular target of IFNs: IFN-β decreased neuronal resting conductance and blocking Ih prevented the increase in input resistance after IFN-β application (Hadjilambreva et al. 2005). In addition, inflammation altered Ih in myenteric neurons (Linden et al. 2003). However, interactions between ion channels and IFNs have not been investigated in detail.

Ih is mediated by HCN channels, which derive from four genes (HCN1–4) found throughout the brain (Santoro et al. 1998). HCN channel subunits generate channels with distinct biophysical properties by assembling to homo- or heterotetrameric complexes (Frere et al. 2004). In neocortical pyramidal neurons, Ih is mainly mediated by HCN1 and HCN2. HCN1 is highly expressed in distal dendrites where it regulates action potential firing patterns (Kole et al. 2006), synaptic integration (Stuart and Spruston 1998; Strauss et al. 2004) and contributes to the subthreshold somato-dendritic voltage attenuation (Zhang 2004) and membrane resonance (Narayanan and Johnston 2008). Modulation of Ih provides a cellular mechanism to alter network oscillations of neural circuits during cognitive processing (Wahl-Schott and Biel 2009). HCN channels are sensitive to a number of intra- and extracellular modulators, which in many cases act by shifting the channel's voltage sensitivity via either cAMP, intracellular protons, phosphatidylinositol-4,5-phosphate or acidic lipids (for review: Wahl-Schott and Biel 2009).

To address whether and, if so, how the neuromodulation by IFNs is mediated via Ih changes, we investigated the effect of type I IFNs on HCN channels of rat neocortical layer 5 neurons. The results show a reduction and deceleration of Ih with consequences for the neuronal frequency behavior. This effect is mediated by the IFN-signaling cascade and specifically governed by a modulation of the fastest activating HCN subunit, HCN1. The data emphasize the role of cytokines in determining the single neuron and network states and present the first direct evidence for a type I IFN action on a neuronal ion channel.

Materials and Methods

Interferons and Signaling Pathway Modulators

For all experiments, Chinese hamster ovary-derived recombinant IFN (rat IFN-α,-β: U-CyTech, Utrecht, The Netherlands; mouse IFN-β: Hycultec GmbH, Beutelsbach, Germany) was used. The lyophilized product was reconstituted in sterile double-distilled water, and small aliquots were stored according to the data sheets. The activation of Janus protein tyrosine kinase (JAK)1 or JAK2 was prevented by the selective blocker substances JAK inhibitor1 and AG-490, respectively (both from Calbiochem, San Diego, CA, United States of America). Blockers were dissolved in dimethyl sulfoxide to 75 or 500 µM, respectively, and stored at −20 °C.

Animals

Male Wistar rats (Forschungseinrichtung für experimentelle Medizin (FEM), Berlin, Germany) and mice (C57/B6/J and B6/129-HCN1tm2Kndl/J, Jackson Laboratory) were bred at the local animal facility. For HCN1−/− experiments B6/129-HCN1tm2Kndl/J were crossed with C57/B6/J, heterozygote offspring were further crossed, and genotyping was performed from tail cuts via polymerase chain reaction (PCR) according to the available protocol (Jackson Laboratory). Animals were kept under standard laboratory conditions, and all procedures were performed in agreement with the European Communities Council Directive of 24 November 1986 (86/609/EEC).

Viral Infection

Anesthetized (ketamine, 100 mg kg−1 intraperitoneal (i.p.); DeltaSelect and xylazine 20 mg kg−1 i.p.; Bayer Health Care, Berlin, Germany) 21-day-old male C57/B6 mice were intrathecally (L2 or L3) injected (Hoffmann et al. 2007) with 20 µL of phosphate-buffered saline (PBS; 3 mice) or 25 µL virus stock (9 mice) containing 106 PFU Theiler's murine encephalomyelitis virus (TMEV) GDVII (Delhaye et al. 2006). Postoperatively, adequate waking and the absence of paresis were verified. Experimental procedures were reviewed by institutional and state authorities (G0175/07).

Slice Preparation and Culture of Cortical Neurons and HEK293 Cells

For a detailed description see Supplementary Methods.

Patch-Clamp Recordings

Individual slices, HEK293 cells, or primary cultures were transferred to a submerged recording chamber. Cortical neurons and HEK293 cells were visualized with either an Axioskop 2 FS Zeiss or an Axiovert S100 (both from Carl Zeiss MicroImaging GmbH, Göttingen, Germany), and whole-cell patch-clamp experiments were carried out at room temperature (RT; 22–24 °C). For the visualization of cortical pyramidal neurons, infrared differential interference contrast video microscopy was used. These experiments were accomplished at 32–34 °C. Patch pipettes were pulled to a final resistance of 3–5 MΩ. In somatic whole-cell voltage clamp, a maximal series resistance of 15 MΩ with changes < 20% during recordings was tolerated. A fast (pipette) capacitive transient (τ < 1.5 μs, 6–13pF) was compensated. The pipette solution contained (in mM): 120 KMeSO4 (ICN Biomedicals, Eschwege, Germany), 20 KCl (Merck), 14 Na-phospocreatine, 0.5 ethylene glycol tetraacetic acid, 4 NaCl, 10 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid, 4 Mg2+-ATP, 0.3 Tris3-GTP with or without 0.1 cAMP (all from Sigma-Aldrich, pH 7.25, 288mOsm). A liquid junction potential of −10 mV has not been corrected for. Voltage-clamp recordings of pharmacologically isolated Ih were obtained by blocking IK(IR) with 200–400 µM Ba2+ added to a modified artificial cerebrospinal fluid: 10 mM K+, MgCl2 replacing MgSO4 (all from Merck), and NaH2PO4 omitted. Sodium currents were suppressed with 1 µM tetrodotoxin (Tocris, Bristol, United Kingdom), low-threshold Ca2+ currents were blocked with 1 mM Ni2+, glutamate receptors were blocked with 20 µM 6-cyano-7-nitroquinoxaline-2,3-dione (both Sigma-Aldrich), and 25 µM D-(-)-2-amino-5-phosphonopentanoic acid (Tocris), GABAA receptors were blocked with 10 µM bicuculline (Tocris), K+ currents (fast-inactivating A-type, IA and delayed rectifier type, IK(DR)) were blocked with 5 mM 4-aminopyridine and 10 mM tetraethylammonium (both from Sigma-Aldrich). Data from all patch-clamp recordings were collected with an EPC-10 (HEKA Elektronik GmbH, Lambrecht, Germany), digitized (10 kHz, after Bessel filtering at 2.5 kHz), and stored using PATCHMASTER software (HEKA). The electrical resonance of the neurons was analyzed with the impedance (Z) amplitude profile (ZAP) method (Narayanan and Johnston 2008). For details see Supplementary Experimental Procedures.

Simulations

For simulations of membrane resonance, we implemented an established model (Hutcheon et al. 1996) in LabVIEW 8.6 (National Instruments Inc., TX, United States of America) and Scilab 5.0.1 (Scilab Consortium, INRIA, ENPC and Contributors, 1989–2008) and utilized a NEURON model (version 7.1; see Supplementary Experimental Procedures) using a reconstructed morphology of a layer 5 pyramidal neuron (Stuart and Spruston 1998, Fig. 1A therein) with properties described in detail in Supplementary Experimental Procedures. The latter was also applied to test the contribution of the different HCN subtypes.

Figure 1.

Infection with neurotopic GDVII strain of the TMEV-reduced hyperpolarization-activated currents (Ih) in mouse pyramidal cortical neurons. (A) Scheme of in vivo IFN induction by intrathecal TMEV/GDVII injection in mice at P21 followed by decapitation and prompt in vitro slice recordings after the first signs of sickness (3–4 days postinjection). (B) Exemplified responses to a family of graded voltage steps (bottom) in neurons from infected (green) and noninfected (black) animals under pharmacological Ih isolation. (C) Top: Comparison of averaged Ih traces of all layer 5 neurons from TMEV- (green) and sham- (black) injected animals at −130 mV. Bottom: Population data and 25–75% box plots. The mean Ih amplitudes (“thick lines through boxes and data”) differed between neurons in slices from noninfected and infected animals (sham: Ih = 1.18 ± 0.50 nA; n = 25 vs. TMEV: Ih = 0.78 ± 0.43 nA; n = 29). Thin horizontal lines within boxes represent the median. (D) Top: Steady-state activation curves constructed from mean relative tail currents upon return to −65 mV from the activation of Ih at different voltages for 2 s, plotted against preceding test voltage in sham- (black) or TMEV- (green) injected animals. Fits of the Boltzmann function are superimposed. Note that the V1/2 shift is not sufficient to effectively reduce the channel availability at voltages below −120 mV. Bottom: Population data of Ih voltage dependence (ctrl: V1/2 = −85.8 ± 3.3 mV, TMEV: V1/2 = −90.4 ± 5.5 mV). *P < 0.05, **P < 0.01, ***P < 0.001 throughout all figures.

Figure 1.

Infection with neurotopic GDVII strain of the TMEV-reduced hyperpolarization-activated currents (Ih) in mouse pyramidal cortical neurons. (A) Scheme of in vivo IFN induction by intrathecal TMEV/GDVII injection in mice at P21 followed by decapitation and prompt in vitro slice recordings after the first signs of sickness (3–4 days postinjection). (B) Exemplified responses to a family of graded voltage steps (bottom) in neurons from infected (green) and noninfected (black) animals under pharmacological Ih isolation. (C) Top: Comparison of averaged Ih traces of all layer 5 neurons from TMEV- (green) and sham- (black) injected animals at −130 mV. Bottom: Population data and 25–75% box plots. The mean Ih amplitudes (“thick lines through boxes and data”) differed between neurons in slices from noninfected and infected animals (sham: Ih = 1.18 ± 0.50 nA; n = 25 vs. TMEV: Ih = 0.78 ± 0.43 nA; n = 29). Thin horizontal lines within boxes represent the median. (D) Top: Steady-state activation curves constructed from mean relative tail currents upon return to −65 mV from the activation of Ih at different voltages for 2 s, plotted against preceding test voltage in sham- (black) or TMEV- (green) injected animals. Fits of the Boltzmann function are superimposed. Note that the V1/2 shift is not sufficient to effectively reduce the channel availability at voltages below −120 mV. Bottom: Population data of Ih voltage dependence (ctrl: V1/2 = −85.8 ± 3.3 mV, TMEV: V1/2 = −90.4 ± 5.5 mV). *P < 0.05, **P < 0.01, ***P < 0.001 throughout all figures.

Quantitative Real-Time PCR

For details see Supplementary Methods.

Immunochemistry

Sagittal brain sections (30 µm) were prepared as described (Kole et al. 2007). The endogenous peroxidase was quenched by 0.3% hydrogen peroxide diluted in PBS for 30 min at RT. After washing, brain sections were blocked with 10% fetal bovine serum (FBS) in PBS overnight at 4 °C. Sections were incubated with anti-IFNAR1 (Abcam, Cambridge, United Kingdom, diluted 1:50 in blocking solution) at 4 °C for 48 h. After washing in PBS, sections were incubated with a biotinylated secondary anti-rabbit antibody (Invitrogen, Darmstadt, Germany) diluted 1:400 in PBS overnight at 4 °C and then in avidin–biotin peroxidase complex reagent (Vectastain ABC Kit, Vector Labs, Burlingame, CA, United States of America) for 2 h at RT. Immunoreaction was visualized with 3,3′-diaminobenzidine as a chromogen. Cultured primary neurons were fixed with 4% paraformaldehyde and 15% sucrose for 20 min at RT. Cells were treated with 20% FBS and incubated with anti-IFNAR1 antibody diluted 1:100 in 5% FBS. After washing with PBS, cells were incubated with a secondary Alexa 488-labeled goat anti-rabbit antibody (Invitrogen; diluted 1:1500). Afterwards, cells were treated with 0.1% Triton X-100 for 3 min and again blocked with 20% FBS. Anti-mitogen-activated protein 2 (MAP2; Sigma-Aldrich) was incubated in a dilution of 1:1500 in 5% FBS. The cells were washed thrice, and Alexa 568-labeled goat anti-mouse antibody (Invitrogen) was added in a dilution of 1:1500. All incubations were performed overnight at 4 °C. Cells were imaged using an upright confocal microscope (DM250, Leica Microsystems CMS GmbH, Mannheim, Germany). For further details and cultures of glial cells see Supplementary Experimental Procedures.

Western Blotting

IFN-β–treated primary neurons and respective controls were lysed in ice-cold buffer (150 mM NaCl, 1% NP-40, 25 mM MgCl2, 10% glycerin, 50 mM Tris, pH 7.4) containing complete protease inhibitor cocktail and phosphatase inhibitors (both Roche, Mannheim, Germany). Protein extracts were separated on SDS–PAGE and electroblotted to a nitrocellulose membrane. Membranes were blocked for 3 h at RT with 5% BSA and incubated with the following antibodies: Anti-p38 MAP kinase 1:1000; anti-phospho-p38 MAP kinase (Thr180/Tyr182) 1:250, anti-phospho-Tyk2 (Tyr1054/1055) 1:1000 (all Cell Signaling, Danvers, MA, United States of America), or anti-Tyk2 1:200 (Santa Cruz Biotechnology, Santa Cruz, CA, United States of America) overnight at 4 °C. Blots were incubated with horseradish peroxidase-conjugated secondary antibodies (1:5000, GE Healthcare, Chalfont St Giles, United Kingdom) overnight at 4 °C, and immunoreactive bands were visualized with chemoluminescence.

EEG

Cortical activity from freely moving Wistar rats was recorded on postnatal days (P)11–12 and from freely moving C57/B6/J and B6/129-HCN1tm2Kndl/J mice on P32–40. For rats: Cortical electrodes were placed and fixed at P10–11 as described previously (Schuchmann et al. 2006) at the following coordinates: 3 mm posterior from the bregma, 2 mm lateral from the midline, with a subdural reference electrode above the cerebellum. Close to the recording electrode, a guiding plastic tube (conical, tip outer diameter 0.9 mm) was implanted above the dura (2 mm posterior from the bregma, 2 mm lateral from the midline; Fig. 8A). After recovery from anesthesia, the pups were returned into their original litter; experiments started earliest 24 h after surgery. The recordings were performed in a specific heated area (32 °C; Supplementary Fig. S8A). The signals were sampled at 0.5–3 kHz using a 12-bit data acquisition board (AD Instruments GmbH, Spechbach, Germany). After a period of exploration (30–60min), the animals started to show increasing silent periods, which were recorded for at least 2 h. Using the implanted guiding plastic tube, we applied rat IFN-β. To reach a large number of neurons and an immediate onset of IFN-β effect, we used a time delayed application technique: The dura was perforated through the implanted guiding tube with a 26-Gauge needle, then we applied 5000 IU IFN-β in 5 µL saline via a 30-Gauge Hamilton syringe into the tubing on top of the perforated dura mater. Using this technique, we avoided any volume effect to the cortex. Subsequently, we recorded again for at least 1h. For the analysis, we only used periods with motorically silent behavior. In control experiments, only saline was applied.

For mice, electroencephalography (EEG) experiments were performed as in rats with slight modifications: Between P30–34 cortical electrodes were placed and fixed 1.5 mm posterior from the bregma and 2 mm lateral from the midline. Saline and IFN-β injections were done in identical animals at least 48 h apart (Fig. 9A) to increase comparability and to reduce animal numbers. Because the mice never were motorically silent, periods showing the least motor artifacts were analyzed.

Statistical Analysis

For all data, statistics were performed depending on the dataset as appropriate in Origin7 (OriginLab, Northhampton, MA, United States of America) or Statview v.457 (Abacus Concepts Inc., CA, United States of America). In detail, for normal distributed datasets (Shapiro-Wilk W-test), we used 2-tailed Student's t-tests. In the case of significant deviations from the normal distribution (P ≤ 0.05) or if the sample size was too small (n ≤ 8) for a reliable test of normal distribution, nonparametric tests were used: Wilcoxon signed-rank test for paired sample sets and Mann–Whitney U-test for unpaired sample sets. Data are presented as mean ± SD.

Results

Viral Infection Inhibits Neocortical Ih

Neurons in mice infected with the neurovirulent GDVII strain of TMEV act as producers of type I IFNs after intrathecal virus application (Delhaye et al. 2006). To test whether in vivo IFN induction by a CNS infection is influencing Ih, we used the TMEV model and performed whole-cell recordings on somatosensory cortex layer 5 neurons at the third or fourth day postinfection (Fig. 1A,B), when animals started to show signs of sickness indicating the elevation of early induced type I IFN levels. TMEV infection reduced the amplitudes of pharmacologically isolated Ih over a broad-voltage range (Supplementary Fig. S1A). At maximum activation (−130 mV), TMEV-reduced Ih amplitudes to 66% in layer 5 neurons (n = 29), compared with such neurons in sham-injected mice (n = 25, P < 0.003, Fig. 1C). Comparing Ih densities to exclude confounding cell-size effects showed a likewise reduction to 77% (P < 0.05, Supplementary Fig. S1B). The current reduction was accompanied by a slightly hyperpolarized voltage dependence of Ih activation (ctrl: V1/2 = –85.8 ± 3.3 mV, TMEV: V1/2 = –90.4 ± 5.5 mV, P < 0.001, Fig. 1D). This shift cannot cause the reduction of maximal Ih, but may increase it at physiological membrane potentials (Fig. 1D, Supplementary Fig. S1A). Thus, type I IFN elevation in a pathophysiological context such as viral CNS infection appears sufficient to inhibit Ih.

Type I IFNs Reduce Neocortical Ih when Applied Acutely and Directly

To study the IFN effect in more detail, we acutely applied recombinant type I IFNs derived from Chinese hamster ovary cells to rat slices containing the somatosensory cortex. The concentration we used (1000 IU mL−1) had an assured effect on neurons (Hadjilambreva et al. 2005) and is in the range observed after systemic viral infections (Heremans et al. 1980). The treatment reduced Ih peak amplitude in all neurons, on average to 80 ± 14% for IFN-α (n = 10, P < 0.05) and to 75.5 ± 19.1% for IFN-β (n = 16, P < 0.001, Fig. 2A) at −130 mV for an example of the entire voltage range (Supplementary Fig. S2A,B).

Figure 2.

Application of type I IFN (1000 IU mL−1) reduced Ih in rat layer 5 neocortical neurons of the somatosensory cortex. (A) Left: Traces of pharmacologically isolated Ih (bottom: Voltage step). Bath application of IFN-α led to an Ih attenuation (blue trace). Middle: Population data, the mean Ih amplitude changed from 1.22 ± 0.57 to 1.00 ± 0.50 nA (n = 10). Right: IFN-β led to a comparable Ih reduction from 681 ± 626 to 521 ± 460pA (n = 16, for responses to a family of graded voltage steps see Supplementary Fig. S1A). Modulation of Ih increased with the IFN dose and occurred over a concentration range from 100 to 10 000 IU (shown for IFN-β in Supplementary Fig. S2D). (B) Steady-state activation curves constructed from mean relative tail currents, plotted against the preceding test potential without (black circles) and with type I IFN (IFN-α blue circles, IFN-β red circles) application. Fits of the Boltzmann function are superimposed. Note, that for statistical comparison steady-state activation curves of each individual neuron were constructed. Inset: Family of tail currents recorded upon return to −65 mV from 2 s voltage steps from −40 to −130 mV. (C) The mean V1/2 did not change upon type I IFN application (left: IFN-α, right: IFN-β). (D) Exemplified time course of the Ih reduction induced by IFN-β (red circles) compared with the time course of Ih in a nontreated neuron (black circles). For long-term stability voltage pulses of −100 mV for 2 s were applied (instead of the maximum of –130 mV shown for most other experiments). (E) The remaining hyperpolarization-activated current after blocking of HCN channels with ZD7288 (50 μM) was stable upon IFN-β application (n = 9), indicating no accompanying change in non-Ih current components. (F) The membrane potential hyperpolarized after IFN-β application from −69.1 ± 0.8 to −72.4 ± 2 mV (n = 9).

Figure 2.

Application of type I IFN (1000 IU mL−1) reduced Ih in rat layer 5 neocortical neurons of the somatosensory cortex. (A) Left: Traces of pharmacologically isolated Ih (bottom: Voltage step). Bath application of IFN-α led to an Ih attenuation (blue trace). Middle: Population data, the mean Ih amplitude changed from 1.22 ± 0.57 to 1.00 ± 0.50 nA (n = 10). Right: IFN-β led to a comparable Ih reduction from 681 ± 626 to 521 ± 460pA (n = 16, for responses to a family of graded voltage steps see Supplementary Fig. S1A). Modulation of Ih increased with the IFN dose and occurred over a concentration range from 100 to 10 000 IU (shown for IFN-β in Supplementary Fig. S2D). (B) Steady-state activation curves constructed from mean relative tail currents, plotted against the preceding test potential without (black circles) and with type I IFN (IFN-α blue circles, IFN-β red circles) application. Fits of the Boltzmann function are superimposed. Note, that for statistical comparison steady-state activation curves of each individual neuron were constructed. Inset: Family of tail currents recorded upon return to −65 mV from 2 s voltage steps from −40 to −130 mV. (C) The mean V1/2 did not change upon type I IFN application (left: IFN-α, right: IFN-β). (D) Exemplified time course of the Ih reduction induced by IFN-β (red circles) compared with the time course of Ih in a nontreated neuron (black circles). For long-term stability voltage pulses of −100 mV for 2 s were applied (instead of the maximum of –130 mV shown for most other experiments). (E) The remaining hyperpolarization-activated current after blocking of HCN channels with ZD7288 (50 μM) was stable upon IFN-β application (n = 9), indicating no accompanying change in non-Ih current components. (F) The membrane potential hyperpolarized after IFN-β application from −69.1 ± 0.8 to −72.4 ± 2 mV (n = 9).

Acute type I IFN induced amplitude reduction was not due to a change in voltage sensitivity. Both the half-maximum activation, V1/2 and the steepness of the activation curve, k were not affected; neither by IFN-α (ctrl: V1/2 = –88.3 ± 3.4 mV vs. IFN-α: V1/2 = –86.6 ± 4.3 mV, P > 0.16; ctrl: k = 10.6 ± 1.0 vs. IFN-α: k = 10.0 ± 2.1, P > 0.06; n = 10) nor by IFN-β (ctrl: V1/2=–88.3 ± 7.5 mV vs. IFN-β: V1/2 = –89.6 ± 7.9 mV, P > 0.16; ctrl: k = 10.6 ± 2.4 vs. IFN-β: k = 10.8 ± 2.2, P > 0.62; n = 16; Fig. 2B,C). As the effect of both type I IFNs appeared similar, results of further experiments are shown just for IFN-β. The reduction in peak amplitude developed surprisingly rapid for a cytokine, starting at about 10 min after IFN-β arrived at the slice and took about 15 further minutes to reach the maximum (Fig. 2D). The peak amplitude partially recovered when IFN-β was washed out (Supplementary Fig. S2AC). In the presence of the specific Ih blocker ZD7288 (50 µM), IFN-β did not change the residual non-Ih mediated, hyperpolarization-evoked currents (at –130 mV: 495 ± 130 vs. 502 ± 154 pA, n = 9, P > 0.86; Fig. 2E), further supporting the idea that the current reduction was specific to HCN channels. Consistent with the contribution of Ih to the resting membrane potential, application of IFN-β hyperpolarized layer 5 neurons by 3.3 ± 2.4 mV (n = 9, P < 0.01; Fig. 2F). The Ih reversal potential, determined from the fully reconstructed current-voltage relationships, did not change due to IFN (tested for IFN-β: ctrl: –20.5 ± 1.4 mV vs. IFN-β: –22.1 ± 5.2 mV; n = 16, P > 0.6), and the effective maximum Ih conductance reduced significantly from 13.1 ± 11.3 to 9.9 ± 8.2nS (P < 0.001, n = 16, Supplementary Fig. S2E). On the whole, these data suggest that IFNs rapidly and reversibly decrease the HCN channel conductance, either by reducing channel number or single-channel conductance.

Ih Reduction is due to a Pronounced Inhibition of HCN1 Channels

In addition to the reduction of the amplitude, type I IFNs decelerated Ih kinetics in rat cortical neurons. The Ih activation was best described by double-exponential fits (Fig. 3A, Supplementary Fig. S3A). IFN-β induced a selective increase in the faster time constant by a factor of 1.31 ± 0.42 (n = 16, P < 0.05), whereas the slower time constant remained the same (Fig. 3B). This was further reflected in the reduction of the relative amplitude contribution of the fast component (0.70 ± 0.09 in ctrl vs. 0.61 ± 0.06 under IFN-β; P < 0.01, Fig. 3C). In conjunction with the slowing of the activation, IFNs prolonged the deactivation of Ih by a factor of 1.5 ± 0.65 (n = 16, P < 0.01, Fig. 3D, Supplementary Fig. S3CE). These effects were qualitatively reproduced by IFN-α (Supplementary Fig. S3C) and partly by TMEV infection (Supplementary Fig. S3H).

Figure 3.

IFN-β (1000 IU mL−1) preferentially reduces fast Ih components in neocortical pyramidal neurons. (A) Ih activation was best described by a double-exponential fit (superimposed fit and corresponding residuals in light gray for a 2 vs. dark gray for a 1 exponential fit; for a statistical comparison see Supplementary Fig. S3A). The corresponding parameters for the displayed double-exponential fits are Afast = 190.9pA, τfast = 178 ms, Aslow = 105.2pA, τslow = 1.248 s. (B) IFN-β decelerates Ih activation as shown by quantitative comparison of the fast (τfast, left) and slow (τslow, middle) activation time constants before and after IFN-β obtained by a −130 mV step. The mean τfast increased from 102 ± 43 to 125 ± 47 ms (n = 16). For an example fit see Supplementary Figure S3B. (C) IFN-β reduced the relative fast component of Ih (Afast/Afast + Aslow) from 0.70 ± 0.09 in control to 0.61 ± 0.06 (n = 16). (D) IFN-β led to a deceleration of the Ih deactivation kinetics estimated from the exponential decline of the tail current at −65 mV after a 2-s hyperpolarizing step to −130 mV (Supplementary Fig. S3C,D). The mean deactivation time constant changed from 211 ± 56 to 310 ± 129 ms.

Figure 3.

IFN-β (1000 IU mL−1) preferentially reduces fast Ih components in neocortical pyramidal neurons. (A) Ih activation was best described by a double-exponential fit (superimposed fit and corresponding residuals in light gray for a 2 vs. dark gray for a 1 exponential fit; for a statistical comparison see Supplementary Fig. S3A). The corresponding parameters for the displayed double-exponential fits are Afast = 190.9pA, τfast = 178 ms, Aslow = 105.2pA, τslow = 1.248 s. (B) IFN-β decelerates Ih activation as shown by quantitative comparison of the fast (τfast, left) and slow (τslow, middle) activation time constants before and after IFN-β obtained by a −130 mV step. The mean τfast increased from 102 ± 43 to 125 ± 47 ms (n = 16). For an example fit see Supplementary Figure S3B. (C) IFN-β reduced the relative fast component of Ih (Afast/Afast + Aslow) from 0.70 ± 0.09 in control to 0.61 ± 0.06 (n = 16). (D) IFN-β led to a deceleration of the Ih deactivation kinetics estimated from the exponential decline of the tail current at −65 mV after a 2-s hyperpolarizing step to −130 mV (Supplementary Fig. S3C,D). The mean deactivation time constant changed from 211 ± 56 to 310 ± 129 ms.

Because acutely applied type I IFNs predominantly decreased the fast component of Ih activation, we assumed an ion channel subtype specificity of the effect, namely a reduction of the fastest activating subtype, HCN1. To test this hypothesis, we used a NEURON model based on a reconstruction of a layer 5 neuron's morphology. In the first instance, we fitted the model parameters (Supplementary Experimental Procedures) to our experimental results before IFN application. We then simulated 2 putative mechanisms of HCN channel inhibition by IFNs: 1) a uniform reduction of both HCN1 and HCN2 channel subtype peak conductances, forumla, versus 2) a specific reduction of the HCN1 channel peak conductance, forumla. To attenuate the Ih amplitude to 76%, as in vitro measured at the soma, we reduced forumla for both settings. This required a combined reduction of forumla to 61.2% or a reduction of forumla to 42.5%. The specific HCN1 reduction mimicked our in vitro experimental results (Fig. 4A): The fast time constant of activation decelerated by a factor of 1.2 (ctrl: τfast = 78 ms; IFN-β: τfast = 93 ms; relative amplitude of τfast: 0.61 vs. 0.59), whereas the slow time constant of activation remained almost unchanged (ctrl: τslow = 451 ms; IFN-β: τslow = 491 ms) and the deactivation time constant increased by 1.6 (ctrl: τ = 212 ms; IFN-β: τ = 340 ms). In contrast, modeling a uniform reduction of both HCN subunit models only marginally increased the time constants of activation (τfast = 88 ms, τslow = 482 ms; relative amplitude of τfast: 0.74) corresponding to an increase by the factor of 1.12 and 1.06, respectively, and the time constant of deactivation rather decreased (τ = 210 ms).

Figure 4.

IFN-β acts via HCN1-mediated current reduction. (A) Simulating IFN-β effects in a morphologically realistic model of a layer 5 neuron (Stuart and Spruston 1998) adjusted to our in vitro control values (black) favor a specific HCN1 reduction: Reducing HCN1 (dashed) mimicked the pronounced increase in τfast, whereas a uniform attenuation of the peak conductance of both channel subtypes (dotted) failed to do so. Inset: HCN density (2/3 HCN1 and 1/3 HCN2) was distributed exponentially across compartments with a 40-times increasing density starting at the soma with 0.95 pS μm−2. (B) Reduction of Ih by 1000 IU mL−1 mouse (m) IFN-β (gray) in HCN1+/+ mice (top) was similar to the one in rat neurons but absent in HCN1−/− mice (middle). (C) Population data of the mouse IFN-β effect on mouse neurons. Whereas mouse IFN-β reduced Ih in HCN1+/+ mice from 829 ± 314 to 590 ± 274pA (n = 8), it failed to do so in HCN1−/− mice (213 ± 119pA in ctrl vs. 202 ± 98pA under mouse IFN-β; n = 8).

Figure 4.

IFN-β acts via HCN1-mediated current reduction. (A) Simulating IFN-β effects in a morphologically realistic model of a layer 5 neuron (Stuart and Spruston 1998) adjusted to our in vitro control values (black) favor a specific HCN1 reduction: Reducing HCN1 (dashed) mimicked the pronounced increase in τfast, whereas a uniform attenuation of the peak conductance of both channel subtypes (dotted) failed to do so. Inset: HCN density (2/3 HCN1 and 1/3 HCN2) was distributed exponentially across compartments with a 40-times increasing density starting at the soma with 0.95 pS μm−2. (B) Reduction of Ih by 1000 IU mL−1 mouse (m) IFN-β (gray) in HCN1+/+ mice (top) was similar to the one in rat neurons but absent in HCN1−/− mice (middle). (C) Population data of the mouse IFN-β effect on mouse neurons. Whereas mouse IFN-β reduced Ih in HCN1+/+ mice from 829 ± 314 to 590 ± 274pA (n = 8), it failed to do so in HCN1−/− mice (213 ± 119pA in ctrl vs. 202 ± 98pA under mouse IFN-β; n = 8).

To test directly whether the HCN1 subunit is required for the IFN-mediated modulation of Ih, we first isolated and then measured Ih in HCN1−/− mice (Nolan et al. 2003) before and after the application of recombinant mouse IFN-β. In accordance with previous studies (Chen, Shu, Kennedy et al. 2009), Ih in neocortical neurons in these mice amounted to one-third of the one in their HCN1+/+ litters (Fig. 4B,C). In line with our model predictions, IFN-β did not affect the remaining Ih in HCN1−/− mice, presumably mediated by HCN2 channels, whereas in control HCN1+/+ mice we observed a similar attenuation as in rats. In detail, 1000 IU mL−1 IFN-β reduced Ih in HCN1+/+ to 71.9 ± 15.4% (P < 0.01, n = 8), but left it unchanged in HCN1−/− (99.7 ± 19.2%, P > 0.4, n = 8).

If HCN channels were composed of homomers, one would expect a distinct V1/2 shift upon selective HCN1 reduction, in particular when the intracellular cAMP levels are low. To test this assumption, we removed cAMP from the intracellular solution. Also under this condition, IFN-β reduced Ih to 73 ± 16% (P < 0.05, n = 6; Supplementary Fig. S3F) without changing the voltage dependence of channel activation (ctrl: V1/2 = –91.2 ± 4 mV vs. IFN-β: V1/2 = –89.1 ± 3 mV, P > 0.24, n = 6; Supplementary Fig. S3G). When rerunning our model adjusted to the data obtained in vitro, where omitting cAMP shifted the control V1/2 by −2.9 mV without reaching the significance levels (P = 0.14, compared with 100 µM cAMP), reducing the HCN1 conductance to 42.5% led to the prediction of a V1/2 shift by −0.88 mV. This is below our experimental resolution limit.

Taken together, these results are consistent with a specific inhibition of HCN1-mediated Ih by type I IFNs.

IFN-β Inhibits Neuronal Ih without Glial Intermediation

To distinguish a direct neuronal modulation from indirect glial effects, we used primary cultured cortical neurons measured at 9–14 days in vitro. In these cultures, the amount of confounding glial cells was reduced to < 5%. Similar to the observations in slices, application of IFN-β to these cultures led to a reduction of the Ih peak amplitude in all cortical neurons to 75.7 ± 14.9% (n = 5, P < 0.05; Fig. 5A). Consistent with the decreased HCN conductance, the input resistance increased on average 14% in current-clamp recordings (P < 0.001, n = 6; Fig. 5A). These results suggest that the subthreshold effects of IFN-β on cortical excitability are directly attributable to neuronal mechanisms.

Figure 5.

IFN-β (1000 IU mL−1) modulates Ih independently of the presence of a proper glial environment but fails to act directly on heterologously expressed cortical HCN channels. (A) Left: Recordings of Ih in a primary cultured cortical neuron showing an amplitude reduction after exposition to IFN-β from 577 (black trace) to 353pA (gray trace). Ih was elicited by a −130 mV voltage step (bottom). Inset: Time course of the Ih reduction. Middle: Quantitative comparison of Ih amplitudes at −130 mV before and after the application of IFN-β for 6–30 min. The mean Ih amplitude decreased from 389 ± 134 to 283 ± 63pA (n = 5). Right: Population data on input resistance obtained by current-clamp recordings on primary cultured neocortical neurons revealed an increase from 645 ± 518 to 721 ± 549 MΩ (7–30 min of IFN-β application, n = 6). (B) Representative traces of Ih mediated by rat HCN1 (left) and rat HCN1/2 (right) overexpressed in HEK293 cells. Ih was elicited by a voltage step to −130 mV (respective bottom). Application of IFN-β (gray trace) did not change Ih when compared with control (black trace) for rat HCN1 (n = 6) or rat HCN1/2 (n = 9). Population data for the Ih amplitudes from rat HCN1 and rat HCN1/2 overexpressing HEK293 cells demonstrate no direct effect of IFN-β on the respective channels (right of the respective traces). Scale bars: 0.25 s; 2 nA.

Figure 5.

IFN-β (1000 IU mL−1) modulates Ih independently of the presence of a proper glial environment but fails to act directly on heterologously expressed cortical HCN channels. (A) Left: Recordings of Ih in a primary cultured cortical neuron showing an amplitude reduction after exposition to IFN-β from 577 (black trace) to 353pA (gray trace). Ih was elicited by a −130 mV voltage step (bottom). Inset: Time course of the Ih reduction. Middle: Quantitative comparison of Ih amplitudes at −130 mV before and after the application of IFN-β for 6–30 min. The mean Ih amplitude decreased from 389 ± 134 to 283 ± 63pA (n = 5). Right: Population data on input resistance obtained by current-clamp recordings on primary cultured neocortical neurons revealed an increase from 645 ± 518 to 721 ± 549 MΩ (7–30 min of IFN-β application, n = 6). (B) Representative traces of Ih mediated by rat HCN1 (left) and rat HCN1/2 (right) overexpressed in HEK293 cells. Ih was elicited by a voltage step to −130 mV (respective bottom). Application of IFN-β (gray trace) did not change Ih when compared with control (black trace) for rat HCN1 (n = 6) or rat HCN1/2 (n = 9). Population data for the Ih amplitudes from rat HCN1 and rat HCN1/2 overexpressing HEK293 cells demonstrate no direct effect of IFN-β on the respective channels (right of the respective traces). Scale bars: 0.25 s; 2 nA.

IFN-β-Induced Ih Inhibition Requires an Intact Canonical Type I IFN Receptor Pathway

Does IFN-β act directly on HCN channels? To address this question, we expressed the prominent cortical HCN channel subunit HCN1 alone and/or together with HCN2 under conditions where the rat IFN-β signaling pathway is negligible. Given the relative insensitivity of human IFN receptors to rat IFN (Novick et al. 1994) and no confounding currents in the hyperpolarizing range (Supplementary Fig. S5B), we chose the HEK293 expression system. This approach revealed that rat IFN-β did not directly affect currents mediated by rat HCN1 (ctrl: 2.25 ± 1.6 nA vs. IFN-β: 2.20 ± 1.5 nA, n = 6, P = 0.35, Fig. 5B left), by rat HCN1/2 (ctrl: 2.39 ± 1.65 nA vs. IFN-β: 2.40 ± 1.67 nA, n = 9, P > 0.93, Fig. 5B right), and by rat HCN2 (Supplementary Fig. S5A) in cells lacking the specific rat type I IFN receptors. The result points to an IFN-β effect mediated by intracellular signaling cascades rather than a direct conformational change in the channel.

IFN-β actions are mediated by 2 transmembrane receptor chains (IFNAR1 and 2) that form the specific type I IFN membrane receptors (IFNARs; Takaoka and Yanai 2006). First, we investigated whether both IFNAR chains are actually expressed by resident cells in the cerebral cortex. Quantitative real-time PCR from cortical tissue showed expression of IFNAR1 and IFNAR2 mRNA. A detailed analysis in primary cultures indicated that both receptor chains are present in neurons, astrocytes, and microglia (Fig. 6A). Immunohistochemical staining of rat cortex revealed IFNAR1 in neurons (Fig. 6B, for antibody specificity see Supplementary Fig. S6A). IFNAR1 staining on primary cortical neurons showed a punctuated immunoreaction in the cell bodies and the dendrites (Fig. 6C). To determine whether this neuronal expression of IFNAR1 is functional, we tested the activation of signaling molecules downstream of the intracellular domain of the IFNAR subsequent to IFN-β binding. The signaling cascade involves Tyk2 and JAK1, both enzymes of the JAK family, and the signal transducers and activators of transcription (STAT)1 and STAT2 (Takaoka and Yanai 2006). Alternate type I IFN signaling pathways operate via the Ca2+-independent di-acylglycerol-mediated protein kinase C pathway or via the MAP kinase pathway, which include p38 and the extracellular signal-regulated kinase 2 (Takaoka and Yanai 2006). For a selective signal cascade analysis, we incubated primary neocortical neurons for 30 min with bath solution containing 1000 IU mL−1 IFN-β. We first probed the canonical pathway, represented by Tyk2, for phosphorylation. Subsequent to receptor activation by IFN-β application, we observed a marked phosphorylation of Tyk2 (Fig. 6D), which points to a proper activation of the early signaling steps. However, the alternative p38 MAP kinase pathway was not activated in neurons, even after 30 min of IFN-β treatment (Fig. 6E). Taken together, we conclude that the IFNAR and its canonical pathway are present and functionally active in neurons.

Figure 6.

The type I IFN receptor (IFNAR) is functionally present on neocortical neurons and constitutes a prerequisite of the Ih attenuation by IFN-β. (A) Quantitative real-time PCR revealed mRNA expression of both IFNAR subunits (IFNAR1 and IFNAR2) in the rat neocortex, primary cultured neurons, astrocytes, and microglia. Data were normalized to glyceraldehyde 3-phosphate dehydrogenase. Normalization to hypoxanthine phosphoribosyltransferase gained similar results. (B) Top and bottom left: Immunohistochemical analysis in the rat neocortex revealed IFNAR1 protein expression in neurons. Top: Arrows indicate neuronal structures, scale bar = 20 µm. Bottom: Slices processed without primary IFNAR1 antibody (scale bar = 20 µm). For antibody confirmation see Supplementary Figure S6A. (C) Co-localization studies with the neuronal marker MAP2 (red) confirmed the IFNAR1 (green) expression in somata and proximal dendritic structures in cultured cortical neurons. As control, neurons were processed without primary IFNAR1 antibody (scale bar = 10 µm). (D) Activation of IFNAR after treatment of primary cortical neurons with 1000 IU mL−1 IFN-β for 30 min was confirmed by phosphorylation of the receptor-associated tyrosine kinase 2 (Tyk2). For (D and E) molecular weight (MW) is given in kDa. (E) IFN-β for 30 min did not change the activation state of p38 MAP kinase, whereas treatment with 2 mM CaCl2 for 10 min readily phosphorylated the enzyme. (F) Inhibition of IFNAR-associated JAK1 prevented the IFN-β–induced change in Ih. Left: Ih traces from a layer 5 neuron under control conditions with 75 nM JAK inhibitor 1 (blue trace) and 30 min after the application of 1000 IU mL−1 IFN-β (red trace) in response to a 2s hyperpolarizing voltage step to −130 mV (bottom). Right: Population data of Ih before (mean: 795 ± 253pA) and after (mean: 797 ± 259pA, n = 12/12) the superfusion with IFN-β.

Figure 6.

The type I IFN receptor (IFNAR) is functionally present on neocortical neurons and constitutes a prerequisite of the Ih attenuation by IFN-β. (A) Quantitative real-time PCR revealed mRNA expression of both IFNAR subunits (IFNAR1 and IFNAR2) in the rat neocortex, primary cultured neurons, astrocytes, and microglia. Data were normalized to glyceraldehyde 3-phosphate dehydrogenase. Normalization to hypoxanthine phosphoribosyltransferase gained similar results. (B) Top and bottom left: Immunohistochemical analysis in the rat neocortex revealed IFNAR1 protein expression in neurons. Top: Arrows indicate neuronal structures, scale bar = 20 µm. Bottom: Slices processed without primary IFNAR1 antibody (scale bar = 20 µm). For antibody confirmation see Supplementary Figure S6A. (C) Co-localization studies with the neuronal marker MAP2 (red) confirmed the IFNAR1 (green) expression in somata and proximal dendritic structures in cultured cortical neurons. As control, neurons were processed without primary IFNAR1 antibody (scale bar = 10 µm). (D) Activation of IFNAR after treatment of primary cortical neurons with 1000 IU mL−1 IFN-β for 30 min was confirmed by phosphorylation of the receptor-associated tyrosine kinase 2 (Tyk2). For (D and E) molecular weight (MW) is given in kDa. (E) IFN-β for 30 min did not change the activation state of p38 MAP kinase, whereas treatment with 2 mM CaCl2 for 10 min readily phosphorylated the enzyme. (F) Inhibition of IFNAR-associated JAK1 prevented the IFN-β–induced change in Ih. Left: Ih traces from a layer 5 neuron under control conditions with 75 nM JAK inhibitor 1 (blue trace) and 30 min after the application of 1000 IU mL−1 IFN-β (red trace) in response to a 2s hyperpolarizing voltage step to −130 mV (bottom). Right: Population data of Ih before (mean: 795 ± 253pA) and after (mean: 797 ± 259pA, n = 12/12) the superfusion with IFN-β.

Both the existence of neuronal IFNAR and the lack of a direct effect of IFN-β on the HCN channel subunits prompted us to investigate whether IFNAR downstream signaling cascades are required to inhibit Ih by testing neuronal IFN-β modulation in the presence and absence of JAK selective blockers. Inhibition of the first signal transduction step within the JAK/STAT pathway prevented the Ih attenuation by IFN-β, as tested by application of IFN-β after pretreatment with 75 nM JAK1 inhibitor (Thompson et al. 2002). Upon such treatment, the amplitude of Ih remained at 101.6 ± 15.9% (n = 12, P > 0.96; Fig. 6F). In contrast, AG-490, a preferentially type II receptor associated JAK2 inhibitor (Meydan et al. 1996), was not effective in blocking the IFN-β modulation of Ih (Supplementary Fig. S6B). These data show that JAK1/Tyk2, but not JAK2 blockade, prevents the IFN-β effect, supporting the hypothesis that the IFN-β effect on neurons requires the JAK1/Tyk2 receptor-signaling pathway.

IFN-β Shifts Neuronal Resonance by Ih Modulation

To test whether the IFN-β–mediated HCN1 channel reduction leads to functionally relevant changes in cellular excitability, we explored the impact of IFN-β on resonance. One function of Ih in pyramidal neurons is to complement passive cell properties in generating a membrane resonance leading to a distinct frequency preference of incoming inputs at rest (Ulrich 2002; Narayanan and Johnston 2008).

To examine whether the magnitude of changes in Ih after rising levels of IFN-β is sufficient to change the resonance behavior, we employed a 3-step approach, starting with an established mathematical model of neuronal resonance (Hutcheon et al. 1996), followed by the application of a morphologically realistic model of a layer 5 neuron, and finalized by experimental testing of the achieved prediction. For the mathematical model, we adjusted parameter values to our experimental data (Supplementary Experimental Procedures). We modeled the effect of IFN-β according to the observed alterations: We 1) reduced forumla to 9.9nS, 2) increased τfast to 0.312 s, and 3) decreased pf to 0.61. This resulted in a resonance frequency shift from 2.23 to 1.76 Hz and an increase in peak impedance (|Z|) from 121.3 to 131.2 MΩ, accompanied by a shift in Φ0 (the frequency where the phase shift plot passes zero) from 1.55 to 1.16 Hz. The subsequently used morphological realistic model of the layer 5 neuron (Supplementary Experimental Procedures) showed similar results when HCN1 was specifically reduced (Fig. 7A,B). Here, the resonance frequency of the membrane shifted from f = 4.52 to 3.3 Hz, the peak impedance increased from |Z| = 36 to 40 MΩ, and Φ0 decreased from Φ0 = 3.0 to 1.95 Hz.

Figure 7.

IFN-β changed the subthreshold membrane resonance of neocortical layer 5 neurons corresponding to in silico predictions based on the in vitro estimated Ih reduction. (A) In silico prediction of changes due to the Ih reduction (gray trace; reduction modeled as estimated in vitro for IFN-β) using the morphologically realistic NEURON model of a layer 5 neuron as presented in Figure 2. Ih reduction decreased the peak impedance frequency and raised the peak impedance. (B) Simulated phase shift plot before and after Ih reduction. Φ0, the frequency where the plot passes zero, shifted to lower frequencies. (C) |IFN-β (1000 IU mL−1) shifted the peak resonance of in vitro whole-cell recorded neurons and increased the maximum impedance. Top: Injected ZAP current (Supplementary Experimental Procedures). Middle: Corresponding voltage recordings from a neuron with a distinct frequency maximum (arrow), which was markedly shifted under the influence of IFN-β (bottom). (D) Left: Respective impedance profile plot (black line) showing a shift of the resonance peak after IFN-β (gray line) from 3.62 Hz/67 MΩ to 3.14 Hz/81 MΩ (n = 9). The population data reveal a marked shift of the resonance frequency in all neurons after IFN-β treatment (middle) accompanied by an increase in the impedance magnitude (right). (E) Left: Respective example of a phase shift plot. The inductive component (i.e. the positive part of the plot, where the voltage leads current) decreases after IFN-β. In this experiment, Φ0 shifted from 2.2 to 1.6 Hz (n = 7). Right: Quantitative comparisons of Φ0 before and after application of IFN-β. (F) The HBW of the impedance profile narrowed after IFN-β treatment.

Figure 7.

IFN-β changed the subthreshold membrane resonance of neocortical layer 5 neurons corresponding to in silico predictions based on the in vitro estimated Ih reduction. (A) In silico prediction of changes due to the Ih reduction (gray trace; reduction modeled as estimated in vitro for IFN-β) using the morphologically realistic NEURON model of a layer 5 neuron as presented in Figure 2. Ih reduction decreased the peak impedance frequency and raised the peak impedance. (B) Simulated phase shift plot before and after Ih reduction. Φ0, the frequency where the plot passes zero, shifted to lower frequencies. (C) |IFN-β (1000 IU mL−1) shifted the peak resonance of in vitro whole-cell recorded neurons and increased the maximum impedance. Top: Injected ZAP current (Supplementary Experimental Procedures). Middle: Corresponding voltage recordings from a neuron with a distinct frequency maximum (arrow), which was markedly shifted under the influence of IFN-β (bottom). (D) Left: Respective impedance profile plot (black line) showing a shift of the resonance peak after IFN-β (gray line) from 3.62 Hz/67 MΩ to 3.14 Hz/81 MΩ (n = 9). The population data reveal a marked shift of the resonance frequency in all neurons after IFN-β treatment (middle) accompanied by an increase in the impedance magnitude (right). (E) Left: Respective example of a phase shift plot. The inductive component (i.e. the positive part of the plot, where the voltage leads current) decreases after IFN-β. In this experiment, Φ0 shifted from 2.2 to 1.6 Hz (n = 7). Right: Quantitative comparisons of Φ0 before and after application of IFN-β. (F) The HBW of the impedance profile narrowed after IFN-β treatment.

Finally, we tested the prediction of the above models in layer 5 pyramidal neurons of acute brain slices. As predicted by our modeling, IFN-β application shifted the membrane resonance to lower frequencies (ctrl: f = 2.3 ± 0.7 Hz, IFN-β: f = 1.9 ± 0.7 Hz, P < 0.001, n = 9) and increased the maximal membrane impedance (ctrl: |Z| = 117 ± 62 MΩ, IFN-β: |Z| =133 ± 70 MΩ, P < 0.05, n = 9; Fig. 7C,D). In further accordance with the model, we observed an apparent reduction of the inductive phase component along with a phase shift of the input impedance (ctrl: Φ0 = 1.3 ± 0.5 Hz, IFN-β: Φ0 = 1.1 ± 0.5 Hz, P < 0.05, n = 7; Fig. 7E). The shift of the resonance parameters to lower values was associated with a narrower range of preferred intrinsic frequencies (half-band width [HBW]ctrl = 3.9 ± 1.4 Hz, HBWIFN-β = 3.2 ± 0.9 Hz, n = 9, P < 0.05; Fig. 7F). The strength of the resonance (Q-value), represented by the ratio of the impedance at the resonant peak to the impedance at rest, remained unaffected (Qctrl = 1.3 ± 0.24 vs. QIFN-β = 1.3 ± 0.15, n = 9, P > 0.32). On the single cell level, IFN-β led to a preference of lower frequencies.

IFN-β Slows the Cortical EEG

Given the impact of IFN-β on resonance behavior in single cerebral pyramidal neurons in our in vitro slice preparation and the role of resonance in setting network activity, we hypothesized that IFN-β affects the oscillatory dynamics of neuronal networks, which appear at the cerebral cortex as EEG rhythms (Karameh et al. 2006). To test this assumption, we applied an effectual amount of IFN-β directly to the rat cerebral cortex in vivo (Fig. 8A, Supplementary Fig. S8A). A deposit volume of 5 µL containing 5000 IU recombinant rat IFN-β was placed right above the cortex while recording the surface EEG in awake motorically silent rats. The diffusion-driven exogenous IFN-β application significantly slowed the cortical EEG activity by ∼0.6 Hz in the frequency range between 2 and 6 Hz (Fig. 8BD). Furthermore, the slowing was associated with a decrease in the power decline from 2.44 ± 0.16 to 1.98 ± 0.18 Hz (n = 6, P < 0.05). The EEG alterations were not due to the experimental methodology, as normal saline without IFN-β had no effect on the EEG power (fctrl = 2.19 ± 0.29 Hz, fsaline = 2.21 ± 0.19 Hz, P = 0.72, n = 4; Supplementary Fig. S8BD).

Figure 8.

IFN-β slows the cortical EEG in rats. (A) Schematic drawing of the experimental setting for rat EEG recordings. Arrows point to the positions of the electrodes, the star indicates the application tube. (B) Representative traces from a P11 rat pup under control conditions (black trace) and after application of 5000 IU IFN-β (red trace). (C) Characteristic power spectrum from motorically silent periods in a rat pup under control conditions (black) and within 30 min after application of IFN-β (red). The decrease of the power was well fitted by single exponential functions (green lines). Inset: Presentation of the frequency difference at a certain power level as a function of frequency under control conditions. (D) Population data on the frequency course given as the e-fold frequency decrease show that IFN-β treatment (n = 6) led to a power decline of the EEG.

Figure 8.

IFN-β slows the cortical EEG in rats. (A) Schematic drawing of the experimental setting for rat EEG recordings. Arrows point to the positions of the electrodes, the star indicates the application tube. (B) Representative traces from a P11 rat pup under control conditions (black trace) and after application of 5000 IU IFN-β (red trace). (C) Characteristic power spectrum from motorically silent periods in a rat pup under control conditions (black) and within 30 min after application of IFN-β (red). The decrease of the power was well fitted by single exponential functions (green lines). Inset: Presentation of the frequency difference at a certain power level as a function of frequency under control conditions. (D) Population data on the frequency course given as the e-fold frequency decrease show that IFN-β treatment (n = 6) led to a power decline of the EEG.

We repeated cortical EEGs in older mice litters (P32–40) from HCN1+/− matings. The effects of exogenous IFN-β application to cortices of HCN1+/+ mice resembled the ones in rats. Here, IFN-β reduced the power of the higher frequencies in the cortical EEG activity, and this was associated with a decrease in the power decline from 2.23 ± 0.62 to 1.40 ± 0.25 Hz (n = 6, P < 0.01; Fig. 9BD, upper row) comparable with the one found in the rats. When applied to cortices of litter HCN1/− mice, however, IFN-β did not alter the EEG (power decline: 1.09 ± 0.20 vs. 1.11 ± 0.23 Hz, n = 7, P = 0.49; Fig. 9BD, lower row).

Figure 9.

IFN-β–induced cortical EEG in mice is prevented by HCN1 channel deficiency. (A) Scheme of the experimental setting for mouse EEG recordings. Arrows point to the positions of the electrodes, the star indicates the application tube. (B) Representative traces from a HCN1+/+ mouse (upper traces) and a HCN1/ mouse (lower traces) after application of saline (gray trace) and 5000 IU mouse IFN-β (red trace). (C) Characteristic power spectrum from the mice shown in B within 30 min after application of saline (gray) and of IFN-β (red). The decrease of the power was well fitted by single exponential functions (green lines). (D) Population data on the frequency course given as the e-fold frequency decrease demonstrate IFN-β–induced power decline of the EEG in HCN1+/+ (n = 6), but not in HCN1−/− (n = 7) mice.

Figure 9.

IFN-β–induced cortical EEG in mice is prevented by HCN1 channel deficiency. (A) Scheme of the experimental setting for mouse EEG recordings. Arrows point to the positions of the electrodes, the star indicates the application tube. (B) Representative traces from a HCN1+/+ mouse (upper traces) and a HCN1/ mouse (lower traces) after application of saline (gray trace) and 5000 IU mouse IFN-β (red trace). (C) Characteristic power spectrum from the mice shown in B within 30 min after application of saline (gray) and of IFN-β (red). The decrease of the power was well fitted by single exponential functions (green lines). (D) Population data on the frequency course given as the e-fold frequency decrease demonstrate IFN-β–induced power decline of the EEG in HCN1+/+ (n = 6), but not in HCN1−/− (n = 7) mice.

These findings suggest that IFN-β modulates spontaneous EEG slow-wave activity depending on the presence of HCN1 and can reversibly alter the physiological responses of cortical neuronal networks.

Discussion

The present study demonstrates that Ih, a major component of intrinsic neuronal excitability, is instrumental in mediating type I IFN-induced changes in neuronal excitability. Extended type I IFN presence as after in vivo induction of IFNs in the CNS by Theiler's virus infection led to an Ih reduction. Also, the acute application of type I IFNs rapidly reduces rodent Ih by about one-fourth. The effect is attributable to a modification of HCN channels, because, first, after blocking Ih no change in current amplitude upon IFN application could be observed, and secondly, synaptic influences or other voltage sensitive currents were excluded by pharmacologically isolating Ih. Based on modeling results and measurements in HCN1/− mice, we conclude that the effect is predominantly mediated by the fast activating HCN subunit, HCN1. Data from primary cultures and the detection of functionally intact IFNAR in neurons revealed that IFN-β directly acts on neurons, that is, without glial mediation.

Interactions of the Signaling Cascades of IFNAR with HCN Channels

Classical signaling in response to IFNAR activation includes a number of phosphorylation steps. Here, we show that cortical neurons possess an essential component of the IFN-signaling cascade, functional IFNAR. Furthermore, the effect of IFN-β on HCN channels requires the activation of the JAK/STAT pathway since IFN-β did not interact directly with HCN channels and was ineffective after disrupting the signaling cascade.

However, the connection between IFNAR activation and HCN channels remains to be demonstrated. One possible link is the p38 MAP kinase, as it can be activated by IFNARs (Takaoka and Yanai 2006) and exerts a direct influence on Ih (Poolos et al. 2006). Nevertheless, 2 lines of evidence in our experiments argue against such an interaction: First, IFN-β failed to phosphorylate neuronal p38 MAP kinase in cortical neurons. This also excludes a contribution of MAP kinase-induced arachidonic acid to be involved in the decrease of maximal current (Fogle et al. 2007). Secondly, IFN-β does not cause a hyperpolarization in the voltage dependence of Ih activation, whereas an upregulation of p38 MAP kinase resulted in an ∼11-mV depolarization of in hippocampal pyramidal neurons (Poolos et al. 2006). Due to the lack of a shift of V1/2, we also exclude an IFN-β/HCN channel interaction through allosteric regulators of voltage dependence of activation such as cAMP, H+, 4,5-PIP2, or signaling lipids (Fogle et al. 2007). A sole protein–protein interaction (i.e. exclusive phosphorylation) appears also unlikely because of the somewhat delayed onset of the effect. Further, the changes of neuronal properties such as input resistance and membrane time constant, which may be linked to HCN channels, were dependent on protein synthesis (Beyer et al. 2009). Therefore, future research on the exact molecular mechanism may be focused on proteins involved in both the IFNAR signaling pathway and HCN modulation and newly transcribed upon IFNAR activation.

The IFN-β Modulation of Ih is Sufficient to Cause Alterations in Functional Properties of Cortical Pyramidal Neurons

Ih is involved in the regulation of neuronal excitability particularly due to its partially open state at resting membrane potential (Wahl-Schott and Biel 2009). Accordingly, the input resistance was markedly increased by IFN-β in neocortical neurons in brain slices (Hadjilambreva et al. 2005) and in primary cultured cortical neurons (this study). Given the distance dependence of the HCN channel density in dendrites of pyramidal neurons (Magee 1998; Kole et al. 2006), an inhibition of HCN channels might lead to an even greater augmentation in dendritic excitability by decreasing the local resting conductance and increasing the summation of excitatory postsynaptic potentials (Magee 1998; Huang et al. 2009). Their local action in dendrites remains to be tested. Of importance for dendritic integration and neuronal computation is the frequency-dependent response of neurons at and below resting membrane potential, for which Ih is the main responsible active current (Ulrich 2002; Narayanan and Johnston 2008). Eventually, resonance describes the frequency dependence of impedance and the band-pass filter characteristics of dendrites for incoming signals (Ulrich 2002). Furthermore, the accompanying phase shift endows neurons to scale the arrival times of signals on the soma (Narayanan and Johnston 2008). Our data suggest that layer 5 neurons favor responses to lower frequency inputs when exposed to elevations in IFN-β. Taken together, these changes point to a significant modulation of neuronal excitability by IFN-β–induced Ih reduction.

Connection between Ih Reduction and EEG Slowing

A number of points suggest that Ih modulation considerably contributed to observed changes in the EEG. As strongest argument, we regard the lack of an IFN-β effect on the cortical EEG of HCN1/− mice (this study). Further, HCN channels exert a global control of neuronal network rhythms (Wahl-Schott and Biel 2009), and the appearance of aberrant EEG activity and seizures is associated with HCN channel reduction (Strauss et al. 2004; Kole et al. 2007; Marcelin et al. 2009). We observed a reduced EEG power in the frequency range between 1 and 8 Hz associated with IFN-β, as it was also reported for Ih inhibition in frontal lobe epilepsy (Marcelin et al. 2009). Karameh et al. (2006) suggested with a modeling approach that cortical alpha rhythms depend on intrinsic currents in layer 5 cells, namely Ih and T-type calcium current. Their study also predicts a pronounced shift to the delta range upon Ih blockade. Furthermore, the sensitivity to synchronized synaptic inputs is promoted by hyperpolarization (Carr et al. 2007) as it is triggered by IFN-β (this study). Interestingly, EEG changes have long been recognized after treatment with IFN-α (Dafny 1983; Birmanns et al. 1990; Kamei et al. 2005), the other type I IFN that also activates signaling via IFNAR.

Pathophysiological Relevance

In the process of inflammation, IFN-β levels are dynamic and dependent on the local environment. Therefore, the concentration used in this study might only represent one within the range of local IFN-β concentrations triggered by inflammation. At present, the precise extracellular type I IFN protein levels that might be expected during a CNS inflammation are unknown, although there are some hints. For example, neuronal IFN-β production in viral infection has been investigated in mice by RT-PCR providing quantitative values of IFN-mRNA production (Delhaye et al. 2006), and a time line of nonspecified IFN tissue content was studied by a 3H-uridine-based assay (Heremans et al. 1980). Quantitative protein analysis of spinal cord homogenate during experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis, showed that IFN-β is expressed at markedly higher amounts in the CNS than in the periphery (Prinz et al. 2008). Given that in inflammation cytokines generally act together, they may combine their impact in vivo, in particular concerning the type I IFNs acting at the IFNAR. Due to the local production (Delhaye et al. 2006), IFNs may activate their respective receptors, even if the tissue concentrations are still quite low. By utilizing the CNS inflammation caused by the neurovirulent GDVII strain of TMEV at the height of type I IFN production (Delhaye et al. 2006), we here showed that viral IFN induction mimic the amplitude reduction in Ih. This supports a pathophysiological role of the type I IFN neuron interaction in CNS inflammation.

Phenomenological similarities between Ih reduction and inflammation provide indirect evidence for a link between both. Pharmacological HCN1 reduction with compounds such as ketamine or several volatile anesthetics (Chen, Shu, Bayliss et al. 2009; Chen, Shu, Kennedy et al. 2009) produces an inflammation-like deteriorated mental state, including disturbed vigilance. Likewise, subtle modulation of HCN channel activity, as observed with physiological changes of cAMP levels, contributes substantially to altered network activity correlated with behavioral states (Wahl-Schott and Biel 2009). In human inflammation states, such functional changes may associate with sickness behavior and an increased susceptibility to depression (Amodio et al. 2005). It was suggested that certain cytokines play a causal role in the genesis of psychosocial alterations (Kent et al. 1992; Dantzer et al. 2008) and that IFN-α therapy can produce such side effects and may contribute to cytokine-related subtypes of affective disorders (Anisman et al. 2008; Dantzer et al. 2008).

Ih modulation by IFN-β may even be of broader importance under physiological conditions given the basic IFN-β level recently reported in the uninfected and noninflamed CNS (Prinz et al. 2008). This would imply a physiological neuromodulatory role of IFN-β.

In summary, our data imply a major role of IFNs in altering the neuronal state during inflammation. This put IFNs in line with previously recognized neuromodulatory cytokines such as IL-2, IL-1β, IL-6, and TNF-α (Mendoza-Fernandez et al. 2000; Dantzer et al. 2008). Taking the contribution of Ih for the proper function of neuronal cells in the nervous system (central and peripheral) into account, our experimental data open up new fields of investigation. These results might shed light on the involvement of Ih alterations in the adaptive processes during acute and chronic neuronal inflammation (Kent et al. 1992; Johnson 2002). Of particular interest will be to determine whether IFNs counteract the frequency response tuning capabilities of neurons, or if they act as a natural protector of brain tissue from inflammation (Prinz et al. 2008) by providing an auxiliary mechanism to adapt neuronal computation to the state of inflammation.

Supplementary Material

Supplementary material can be found at: http://www.cercor.oxfordjournals.org/.

Funding

This study, in particular the work of K.S. and U.S., was supported by the German Research Foundation (DFG STR865/3-1) and the DAAD/Go8 program (U.S. and M.H.P.K.). Some of the equipment used was donated by the Sonnenfeld-Stiftung, Berlin (A.U.B. and U.S.).

Notes

We thank Bettina Brokowski, Carla Strauss, and Rike Dannenberg for expert technical assistance, Shigetada Nakanishi for the donation of rHCN2, and Thomas Michiels for advice on the induction of the viral encephalomyelitis and for providing TMEV GDVII. We also thank Arndt Rolfs for providing us with laboratory space, consumables, and equipment in the initial phase. Conflict of Interest: None declared.

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Author notes

K.S. and C.B. contributed equally to this work.